Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-25T05:21:17.034Z Has data issue: false hasContentIssue false
  • English
  • Français

Optimisation analysis of reinforced cable distribution on the airship

Published online by Cambridge University Press:  07 October 2021

H. Zhao ,
Z. Chen Open the ORCID record for Z. Chen [Opens in a new window]  and
J. Chen
H. Zhao
Affiliation:
School of Aeronautics and Astronautics, Shanghai Jiaotong University, Shanghai, China
Z. Chen*
Affiliation:
School of Aeronautics and Astronautics, Shanghai Jiaotong University, Shanghai, China
J. Chen
Affiliation:
School of Aeronautics and Astronautics, Shanghai Jiaotong University, Shanghai, China
*
Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Reinforced cables are usually installed on flexible airship structures to enhance their load-bearing capability. However, reinforced cables also increase the total weight of the airship. In order to find a balance between large loading-bear capability and light weight, a multi-objective optimisation scheme based on the genetic algorithm NSGA-II is put forward for the reinforced cable distribution on the airship. Firstly, different cable distribution schemes are presented according to engineering experience and the optimal one is determined by load analysis. Then, the CAE method and optimisation analysis are combined to achieve structure design optimisation. The parametric model of the airship structure with reinforced cables is established by ABAQUS secondary development and the load analysis is carried out. Parameter passing and optimisation algorithm are operated by Isight software and the optimisation analysis is conducted based on the NSGA-II algorithm. Finally, we draw some conclusions of the rules of optimised reinforcing cable distribution. The work of this paper has crucial engineering significance for improving performance of the airship structure design.

Keywords

AirshipCable distribution optimisationCable-membraneABAUSNSGA-||
Type
Research Article
Information
The Aeronautical Journal , Volume 126 , Issue 1298 , April 2022 , pp. 607 - 616
Check for updates
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ceruti, A., Voloshin, V. and Marzocca, P. Multi-Disciplinary Design Optimization of Unconventional Airship Configurations with Heuristic Algorithms, AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, & Materials Conference, 2013. doi: 10.2514/6.2013-1676.CrossRefGoogle Scholar
Ceruti, A., Voloshin, V. and Marzocca, P. Heuristic algorithms applied to multidisciplinary design optimization of unconventional airship configuration, Journal of Aircraft, 2014, 51, (6), pp 1758–1772. doi: 10.2514/1.c032439.CrossRefGoogle Scholar
Kanikdale, T. Optimization of airship envelope shape using computational fluid dynamics, Indian Institute of Technology, Bombay, 2004.Google Scholar
Kanikdale, T., Marathe, A. and Pant, R. Multi-disciplinary optimization of airship envelope shape, AIAA/ISSMO Multidisciplinary Analysis & Optimization Conference, 2013. doi: 10.2514/6.2004-4411.CrossRefGoogle Scholar
Ram, C.V. and Pant, R.S. Multi-Disciplinary shape optimization of aerostat envelopes, Journal of Aircraft, 2010, 3, (47), pp 1073–1076.CrossRefGoogle Scholar
Yang, Y., Wang, S., Gu, Y., et al. The optimization design and simulation of adjacent space airlift shape, Chinese Space Science and Technology, 2011, 31, (5), pp 76–83. doi: 10.3780/j.issn.1000-758X.2011.05.011.Google Scholar
Zhang, X. and Zhang, A.W. Shape optimization of airship based on constrained particle swarm optimization, Journal of Information & Computational Science, 2013, 10, (18), pp 5849–5857.CrossRefGoogle Scholar
Nan, B. Refined Analysis and Light-Weight Design of Semi-Rigid Stratospheric Airship Frame Structures, 2015.Google Scholar
Shengqi, C. and Haifeng, W. Parameter Calibration design of high-altitude airlift propulsion system. Journal of Northwestern Polytechnical University, 2013, 31, (4), pp. 530–534. doi: CNKI:SUN:XBGD.0.2013-04-007.Google Scholar
Chen, S., Song, B. and Wang, H. Exploring optimum power unit of propulsion system for high altitude airship, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2015, 229, (2), pp 301–311.CrossRefGoogle Scholar
Wasserstein, R.L. Monte Carlo: Concepts, Algorithms, and Applications, by Fishman, G.S., Springer-Velag, 1996.Google Scholar
Storn, R. and Ptice, K. Differential evolution–A simple and efficient heuristic for global optimization over continuous spaces, Journal of Global Optimization, 1997, 11, (4), pp 341–359. doi: 10.1023/a:1008202821328.CrossRefGoogle Scholar
Hoos, H.H. and Stutzle, T. Stochastic Local Search: Foundations and Applications, Stochastic Local Search: Foundations & Applications. Morgan Kaufmann Publishers Inc. 2004. doi: 10.1007/3-540-36440-4_20.Google Scholar
Kennedy, J. and Eberhart, R. Particle swarm optimization, Proceedings of ICNN95-International Conference on Neural Networks. IEEE, 1995. doi: 10.1109/ICNN.1995.488968.CrossRefGoogle Scholar
Kaveh, A. Imperialist Competitive Algorithm, Springer International Publishing, 2017. doi: 10.1007/978-3-319-46173-1_11.CrossRefGoogle Scholar
Su, J. and Jiang, B. Second Development of ABAQUS Python Introduction, Post & Telecom Press, 2016.Google Scholar
Saito, Y., Iijima, I., Matsuzaka, Y., et al. Development of a super-pressure balloon with a diamond-shaped net, Advances in Space Research, 2014, 54, (8), pp 1525–1529. doi: 10.1016/j.asr.2014.06.043.CrossRefGoogle Scholar
Tu, Y. Multi-spherical-surface geometric configurations and analyses of inflatable combined cable–membrane structure for lunar habitation, Advances in Space Research, 2015, 56, (7), pp 1281–1287. doi: 10.1016/j.asr.2015.06.027.CrossRefGoogle Scholar
Nakashno, K., Saito, Y., Goto, K., et al. Super pressure balloon with diamond-shaped net: A numerical study of its structural characteristics, 4th AIAA Spacecraft Structures Conference, 2017, 1117. doi: 10.2514/6.2017-1117.CrossRefGoogle Scholar
Lai, Y. and Jiang, X. Theory of Isight Parameter Optimization and detailed example explanation, Beihang University Press, 2012.Google Scholar
Deb, K., Agrawal, S., Pratap, A., et al. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, Evolutionary Computation, 2000, 1917, pp 849–858. doi: 10.1007/3-540-45356-3_83.Google Scholar
Zhang, Z., Liao, C., Chai, H., et al. Multi-objective optimization of controllable configurations for bistable laminates using NSGA-II, Composite Structures, 2021, 266, p. 113764. doi: 10.1016/j.compstruct.2021.113764.CrossRefGoogle Scholar
Supplementary material: File

Zhao et al. supplementary material

Zhao et al. supplementary material

Download Zhao et al. supplementary material(File)
File 663.2 KB